INSTITUTE FORECOLOGICALECONOMICSVienna University ofEconomics and Business

Working Paper Series2/2015

Syed Ali Asjad NAQVI

Modeling Growth, Distribution,and the Environment in a

Stock-Flow Consistent Framework

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Modeling Growth, Distribution, and the Environment in a

Stock-Flow Consistent Framework∗

Asjad Naqvi†

February 6, 2015

WORKING PAPER

Abstract

Economic policy in the EU faces a trilemma of solving three challenges simultaneously

growth, distribution, and the environment. In order to assess policies that address these

issues simultaneously, economic models need to account for both sector-sector and sector-

environment feedbacks within a single framework.This paper presents a multi-sectoral stock-

ow consistent (SFC) macro model where a demand-driven economy consisting of multiple

institutional sectors rms, energy, households, government, and nancial interacts with

the environment. The model is calibrated for the EU region and ve policy scenarios

are evaluated; low consumption, a capital stock damage function, carbon taxes, higher

share of renewable energy, and technological shocks to productivity. Policy outcomes are

tracked on overall output, unemployment, income and income distributions, energy, and

emission levels. Results show that investment in mitigation technologies allows for absolute

decoupling and ensures that the above three issues can be solved simultaneously.

Keywords: ecological macroeconomics, stock-ow consistent, growth, distribution, environment, European Union

JEL: E12, E17, E23, E24, Q52, Q56

∗This research is supported by the EU FP7 grant titled WWWforEurope (290647). Earlier versions of thispaper greatly beneted from feedback provided by Rudi von Arnim, Jeroen van den Bergh, Duncan Foley,Antoine Godin, Tim Jackson, Stephen Kinsella, Kurt Kratena, Miriam Rehm, Malcolm Sawyer, Sigrid Stagl,Klara Zwickl, participants at the WIFO Modeling Workshop, the University of Limerick Environmental ModelingWorkshop, and the AK Wien, FMM, and the EAEPE conferences. All errors are my own.†Post-doctoral researcher, Institute for Ecological Economics, Department of Socioeconomics, Vienna Univer-

sity of Economics and Business (WU), Austria. snaqvi@wu.ac.at.

1

1 Introduction

After the 2008 nancial crisis, real output in the European Union (EU) has stagnated while

unemployment has crossed the 10% mark (Figure 1.1a). This raises important challenges in

addressing issues of inequality and the burden on the welfare state that is set up to ensure a

minimum standard of living (European Commission 2014a). The EU is large fairly closed econ-

omy, 90% of total output is consumed within its boundaries with almost 60% of it attributed

to household consumption (1.3). Thus any form of demand creation will result in alleviating

to some extent both the growth and the unemployment issue. However, output and energy use

are also highly correlated (Figure 1.1b), implying that any increase in demand will increase en-

ergy consumption and emissions, a phenomenon referred to in literature as the rebound eect

(Binswanger 2001; Jackson 2009; Wiedmann et al. 2013). In light of this, the recently proposed

2030 Kyoto targets of reducing emissions by 40% with a 27% renewable energy becomes an

ambitious outcome especially if growth, low employment, and equity are also to be addressed

simultaneously (European Commission 2014b, p. 19). Thus if the EU is to achieve its energy

targets, absolute decoupling (Jackson 2009) becomes a necessary condition while growth and

employment have to accommodate structural adjustments to the economic setup (Foley and

Michl 1999; Taylor 2004). In short, the macro level policy challenge for the EU can be ab-

stracted to a growth-distribution-environment trilemma that needs to be solved simultaneously

(Kronenberg 2010; Spash 2012; Fontana and Sawyer 2013).

Figure 1.1: EU macro indicators

(a) (b)

In order to address the above issues, a multi-sector macro model is developed in this paper

in a stock-ow consistent (SFC) demand driven framework (Godley and Lavoie 2007; Lavoie

2009; Caverzasi and Godin 2013) with supply side environmental constraints (Kronenberg 2010;

Fontana and Sawyer 2013). The SFC framework represents a closed monetary economy where

dierent sectors interact endogenously through behavioral decision making rules to generate

economic activity while also satisfying double entry accounting principles (Taylor 2004; Godley

2

Figure 1.2: EU GDP Composition

Figure 1.3: By sectors

and Lavoie 2007; dos Santos and Zezza 2008). This implies that the inow of one sector has

to be exactly matched by the outow of another in a fully tractable monetary system. Stocks

represent the net worth of sectors at discrete time periods (for example one year) while ows

represent all transactions between two time periods. This water-tight framework ensures ows

are not generated in a vacuum but are carefully tracked across all sectors of the economy in a

fully tractable closed economic framework. Tables B.1 and B.2 give an example of the stocks

and ows of the household sector in the European Union for a one year time period. A key

advantage of this framework is that the impact of policies can be tracked across all sectors of the

economy. This allows for capturing all positive and negative feedback eects that might result in

counter-intended policy outcomes. While recent applications of SFC models have mostly been

used to understand sectoral imbalances in the wake of the recent of nancial crisis (dos Santos

and Zezza 2008; Le Heron and Mouakil 2008; van Treeck 2009; dos Santos and e Silva 2009;

Chatelain 2010; Kinsella and Khalil 2011), some eorts have been made to integrate economic

issues with environmental constraints (Godin 2012; Berg et al. 2015).

The paper proposes two key innovations in the ecological economics modeling literature. First,

it endogenizes the relationship of multiple sectors in the economy within a single framework.

This implies that interactions among the rms, energy sector, households, the government, and

the nancial sector are fully captured which allows for incorporating cross-sectoral feedbacks of

various policies. This approach deviates from the other models which exclusively focus on output

and growth without fully addressing issues of unemployment and distribution. Second, the

model endogenizes the relationship of the real economy and the environment. This is captured

through material ows that directly impact the real economy through resource extraction costs

and emissions that accumulate in the environment and can aect capital stock and output. This

is a deviation from conventional environmental models which discuss the environment damage

3

as an exogenous negative externality that can be solved through market-based pricing (Stern

2007; Weitzman 2009; Yohe et al. 2009; Hope 2011; Pindyck 2013), calculating social costs of

carbon (Nordhaus 2011; Pindyck 2013; Foley et al. 2013), or through carbon taxes (Herber and

Raga 1995; Marron and Toder 2014). Thus agents are allowed to damage the environment as

long as they can aord to pay the monetary cost without fully addressing planetary boundaries

(Rockström et al. 2009).

Within a non-mainstream framework, several models have emerged in recent years that aim

to address the issues of the impact of climate on the economy and vice versa. These have

signicantly contributed to topics including building a sustainable growth friendly nancial

sector (Fontana and Sawyer 2014), modeling emissions using an endogenous growth theory with

business cycles (Taylor and Foley 2014), modeling environmental damage as an endogenous

global negative externality (Rezai et al. 2012), setting up a green sector with guaranteed full

employment (Godin 2012), linking households nancial portfolio decisions with environmen-

tal indicators (Victor and Jackson 2013), and combining input-output material ows with the

prices and interest rates in a stock-ow consistent framework (Berg et al. 2015). This model

contributes to these class of models by providing a complete economic and environment account-

ing framework for the production, or the real-real side, of the economy that allows for policy

tracking. Thus in the model, the focus is kept directly on production decisions and household

demand formation while a very simple nancial sector is introduced. This keeps the model sim-

ple and tractable while also focusing on direct household related issues including employment,

real income levels and functional income distributions.

Five policy experiments proposed in the ecological economics literature are conducted on a model

calibrated to the EU economy. The rst experiment looks at a de-growth scenario based on the

limits to growth hypothesis (Meadows and Club of Rome 1972; Jackson 2009; Victor 2012).

This hypothesis suggests that policy driven reduction in output will result in lower energy use

and subsequently lower emissions. The second experiment introduces a damage function that

endogenizes the depreciation of capital stock to the level of emissions (Tol 2002; Stern 2007;

Hope 2011; Nordhaus 2011; Rezai et al. 2012). This . The third experiment highlights the

costs of shifting to a higher share of low-emissions high-cost renewable energy (Trainer 1995;

Dincer 2000; Tahvonen and Salo 2001; Varun et al. 2009). The fourth experiment introduces

carbon taxes on rms and households (Herber and Raga 1995; Marron and Toder 2014). The

fth experiment discusses technological innovation and resource eciency that aims to address

issues of growth in an absolute decoupling scenario (Binswanger 2001; Yang and Nordhaus

2006; Herring and Roy 2007). The model outputs track output and growth with other key

macroeconomic indicators including unemployment, income and income distributions, prices,

energy, and emissions.

The paper is organized as follows. Section 2 sets up the framework and Section 3 explains

the model in detail. Section 4 describes policy scenarios and the simulation results. Section 5

concludes. Behavioral equations of the nancial sector are discussed in Appendix D.

4

2 Framework

Figure 2.1 summarizes the relationships between four economic sectors in the model pro-

duction, households, government, and the nance sector - and one environment sector. The

production sector is taken as a macro institution that produces both capital and consumption

goods where output is determined through demand by household consumption, government ex-

penditure, and rm investment. This demand generation is supported by banks in the form of

deposits, loans and advances to form a complete circular ow economy. The production process

requires three complimentary inputs; capital, labor, and energy. Capital is generated through

investment, worker households provide labor, while energy is supplied by energy producers.This

allows the rms and the energy sector to be dual-linked through energy demand and prices. En-

ergy supply is generated from an exogenously determined mix of non-renewable and renewable

energy.

The real economy is integrated with the environment through two channels. First, energy

production requires a non-renewable input that depletes over time and second, Greenhouse Gas

(GHG) emissions, generated through the production process, accumulate in the atmosphere.

Figure 2.1: Model layout

5

In order to account for dierences in the functional income distribution, two household classes are

introduced in the model. Capitalists, as owners of capital (rms, energy, banks)who earn prot

income and workers as owners of labor who earn wage income if employed or unemployment

benets if unemployed. Real disposable income determines consumption levels while savings are

kept in commercial banks. Commercial banks give out loans to the Production sector. If demand

for loans exceed deposits, Commercial banks can request advances from the central bank which

results in the creation of endogenous money (Moore 1988; Starr 2003; Keen 2014; Lavoie 2014a).

The government earns tax revenue from rms, households and the nancial sector which it uses

to fund public sector investment and unemployment benets. If a decit exists, it is nanced

by issuing short-term Treasury Bills.

Following the accounting framework presented in Godley and Lavoie (2007), economic activities

are tracked in two monetary accounts, a balance sheet and a transition ow matrix (TFM). The

balance sheet is given in Table A.1 where the columns show the net worth of the economy across

dierent institutional sectors at the end of each of a time period. Interactions between agents

results in ows between two time period which are summarized in the transition ow matrix in

Table A.2. Double entry accounting restrictions imply that all rows and columns must add up

to zero. Columns represent the sources and uses of funds for each agent category. For example,

the worker's column in the TFM shows wages and interest earnings on deposits as inows while

taxes and consumption are outows. Savings results in changes in bank deposits which are also

reected as change in the balance sheet. As an example, Appendix B shows how stocks and

ows for the household sector evolve in the EU over a one year period.

3 Model

This section gives the behavioral rules of the agent categories using the following system of

notations; capital letters are used to represent nominal (current) value in money while lowercase

letters represent real values or stocks. For dierent agent categories, the same variables are

super-scripted using h for workers, k for capitalists, u for unemployed, f for rms, X for non-

renewable energy, R for renewable energy, b for commercial banks, CB for the central bank, and

g for government. Time is denoted with a subscript t and exogenous parameters are written

using Greek symbols. ∆ represents a rst order dierence.

3.1 Firms

The rms sector in the model produces both consumption and capital goods based on demand

from households, government and the production sector's investment decisions. Assuming full

information about current demand with adaptive expectations, the rm's total real output yt

equals total sales st plus changes in stock of inventories int (3.1).

6

yt = st + ∆int (3.1)

st =(ckt + cht + cut

)+(it + iXt + iRt

)+ Ω (3.2)

∆int = γ(σst−1 − int−1) (3.3)

Total sales are calculated as the total consumption demand by households (capitalists, workers,

unemployed), investment decisions of the rms and the two energy sectors plus the governments

autonomous expenditure Ω. Change in inventories, ∆int are determined as a fraction γ of the

gap between target inventories, determined as ratio σ of past sales, minus inventories at the start

of the period. Firms hold inventories to hedge against any unexpected changed in demand.

The production process requires three complimentary inputs; labor, capital and energy. The

demand for labor Nft is determined by total output produced over the exogenously dened labor

productivity per unit of output ξY N . The total wage bill (3.5) is calculated as total workers

hired times the exogenous wage rate ω.

Nft =

ytξY N

(3.4)

WBt = Nft .ω (3.5)

Similar to labor demand, energy demand is determined by total output over the capital-to-

energy productivity ratio ξY E (3.6). The total energy bill is determined as the total energy

demand times the price of energy pEt (3.7).

Et =ytξY E

(3.6)

EBt = Et.pEt (3.7)

Firms actual capital stock in use to produce output is determined by the capital-to-output ratio

ξY K

kt =ytξY K

(3.8)

Firms, as part of their liquidity preference strategy, keep a certain proportion of their capital

stock slack in order to adjust to changes in demand. The decision to invest in capital stock is

determined through an accelerator function (Jorgenson 1963; Taylor 2004; Storm and Naastepad

2012; Lavoie 2014b) driven by the target capacity utilization ratio ν. Actual investment it is

determined by two parameters; capital depreciation rate δ, and the rate of investment β, and

the gap between current capacity utilization rate ut and the target capacity utilization rate ν.

7

it = Max[β(ut − ν) + δ, 0]kt−1 (3.9)

The value of the investment it (3.9) is bounded below by zero implying that negative invest-

ment in capital is not allowed. The expression in equation 3.9 gives three investment regions;

rms increase capital stock if demand increases (ut > ν), rms invest to maintain at least the

depreciation value it = δ of capital stock if demand doesn't change (ut = ν), and rms don't

invest at all (it = 0) if demand goes down and capital is under utilized. In this scenario, capital

stock is allowed to depreciate in value.

Current capacity utilization (3.10) is described as the current output divided by maximum

potential output yt.

ut =ytyt

(3.10)

yt = ξY Kkt−1 (3.11)

Assuming rms are fully leveraged and money is readily available from commercial banks, the

current nominal value of loans requested by rms equals the nominal value of expected change

in inventories ∆INt = UCt∆int and the nominal value of capital stock investment It = itpt.

Thus the demand for loans can be written as:

Lft = It + ∆INt (3.12)

Rft = λLt−1 (3.13)

Every time period, a fraction λ of past loans is repaid to the banks.

From equations 3.5, 3.7 and 3.13, the unit cost per unit of output can be derived as:

UCt =WBt + EBt +Rf

t

yt(3.14)

pt = UCt(1 + θ)(1 + τF ) (3.15)

Prices are determined through an exogenous markup θ over unit costs and the tax rate τF . Thus

an increase in wages, energy prices and loans would add to the costs and subsequently prices

within the economic system feeding back on demand.

Firms realized prots thus equal:

Πft = St(1− τF ) + ∆INt −WBt − EBt −Rf

t − (rlLft−1) (3.16)

8

where the rst term above gives the nominal value of sales St = stpt minus taxes. The last

term represents the interest paid to commercial banks based on past loans. The prots are fully

redistributed to the capitalists.

3.2 Energy Sector

The energy sector supplies uniform energy to rms produced through two sources. A non-

renewable input dependent high emissions energy and a zero emissions renewable resource de-

pendent capital intensive energy. The share of non-renewable energy in total supply is exoge-

nously determined by the parameter φ. The energy sector mirrors the production sector with

two key exceptions. First, the energy sector's investment decision to expand production capital

adds to the demand of the rms. Second, the energy sector has an endogenous own energy

consumption cost to produce energy demanded by rms.

Non-renewable energy production requires a non-renewable input X, a resource that has to be

extracted from the environment. The quantity of X required to meet this demand, or indirect

sales of X to rms is given as:

sXt =φEt

ξXE(3.17)

where ξXE is the X-to-non-renewable energy ratio. In order to produce energy the non-

renewable sector requires to consume energy as well. Total output of X is given as:

yXt = sXt (1 + ηX)

where ηX is the share of energy required for own consumption.

Assuming energy cannot be stored, the energy sector holds inventories of the non-renewable

input X to smooth out unexpected changes in energy demand. The stock of X extracted every

time period is given as:

Xt = yXt + ∆inXt (3.18)

or the total sales plus changes in inventories of X determined by the inventories to sales ratio σ

following the same procedures as dened for rms in equation 3.3.

The non-renewable energy sector faces two costs: an extraction cost determined per unit of

output as κX and the own cost of consumption determined as a fraction η of total sales.

XCt = κX .Xt (3.19)

OCXt = ηXsXt (3.20)

9

From this the unit cost for the non-renewable energy sector can be derived as:

UCXt =

XCt +OCXt

yXt(3.21)

For the renewable energy sector, the total demand equals the total share of energy output

produced by the renewable sector.

sRt = (1− φ)Eft (3.22)

yRt = sRt (1 + ηR) (3.23)

The total output produced is a fraction ηR of total demand to accommodate own consumption.

For simplicity we assume that the only cost renewable energy sector faces is its own cost of

consumption given as:

OCRt = ηRsRt (3.24)

UCR =OCR

t

yRt(3.25)

In order to ensure that the renewable energy sector is more expensive than the non-renewable

sector own costs in the renewable energy sector are higher than those of the non-renewable

sector such that ηR > ηX .

The price of energy, pEt is derived as follows:

pEt =(φUCX

t (1 + τX) + (1− φ)UCR(1 + τR))

(1 + θ) (3.26)

This is a simple weighted average of the unit cost adjusted for energy sector industry specic

taxes, τX and τR times the xed mark-up θ. Assuming ηR > ηX (3.26) implies that as the

share of renewable energy in total energy supply goes up, the price of energy will increase as

well. Prots from both non-renewable and renewable, ΠXt and ΠR

t are fully redistributed to the

capitalists.

3.3 Environment

The environment is introduced in the model as providing the non-renewable resource X through

extraction from the ground and as absorbing Greenhouse Gases (GHGs) in the atmosphere. The

resource depletion rate RDt of the non-renewable input is already dened in 3.27

10

RDt =X

X −∑t−1

i=0 Xi

(3.27)

X is the quantity of the nite stock of non-renewable input while the denominator gives the

current value of the non-renewable input left in stock. The function implies that extraction

costs have a negligible impact on prices if a relatively small proportion of the non-renewable

resource has been extracted. Costs increase exponentially as X nears depletion. This extreme

condition is not explicitly discussed in this paper.

GHGs are assumed to accumulate at a linear rate relative to the level of rm production and of

high emission energy sector production. The increase in stock is formalized as:

GHGt = GHGt−1(1− φ) +yt + yXtξY G

(3.28)

where φ is an exogenously dened parameter representing the absorption capacity of GHG into

the environment or the natural carbon cycle (IPCC 2007, 2012). ξY G is the emissions-to-output

ratio indexed to a baseline value.

3.4 Households

Households are composed of capitalists and workers. In the model, all household agent categories

are assumed to follow the same decision making procedures. The key dierence lies in the income

source:

Inckt = Πf + ΠXt + ΠR

t + Πbt + rdD

kt−1 (3.29)

Incht = WBt + rdDht−1 (3.30)

Incut = UBt (3.31)

Capitalists earn prot income from the production and nancial sector plus interests on bank

deposits (3.29). Employed workers earn wages plus interest income from deposits (3.30), while

the unemployed households receive transfers from the government (3.31).

Given a total xed labor force of N , unemployed households are simply workers not employed

by the rm sector (3.32).

Nu = N −Nft (3.32)

ubt = Nu.ε (3.33)

11

The unemployed households Nu are expected to maintain a socially dened minimum level of

consumption ε in the form of unemployment benets ubt (3.33) where the nominal value of the

transfer program is given as:

UBt = ubt.pt (3.34)

Household income after tax τh gives the disposable income as follows:

Y Dt = Inct(1− τh) (3.35)

Households make consumption decisions based on real income and wealth levels. The consump-

tion decision in real terms is dened as:

ct = α1ydt−1 + α2vt−1 (3.36)

where ydt and vt are real values of disposable income and wealth, and α1 and α2 are the

marginal propensities to consume out of income and wealth respectively. Disposable income net

of consumption results in a change in nominal wealth:

∆Vt = Y Dt − Ct (3.37)

All savings after tax and consumption are deposited in banks which gives the net worth of the

households.

Dt = Vt (3.38)

3.5 Government

The government plays two important roles in the model. First it is required to make consumption

expenditures to maintain social infrastructure and investment. Government consumption is

dened exogenously as Ω which in nominal terms equals

Gt = Ω.pt (3.39)

Second, it ensures a minimum consumption level for the unemployed such that the total unem-

ployment benets bill is UBt (3.34). This expenditure is nanced through tax revenues that it

earns from the rms and the households where the total taxes collected equal:

Taxt = T ft + TX

t + TRt + T k

t + Tht (3.40)

12

If the tax revenue is not sucient to nance the government expenditure then the government

issues treasury bills, TBt. The government's debt or borrowing requirement BRt is dened as:

BRt = Gt + UBt + rbTBt−1 − Taxt −ΠCBt (3.41)

∆TBt = BRt (3.42)

where rbTBt−1 is the interest owed on past treasury bills issued and ΠCBt are central bank

prots redistributed to the government. New treasury bills issued equal the government debt

requirement (3.42). In the model all bills are assumed to be purchased by the central bank

and thus central bank prots include interest earnings on advances to commercial banks and

treasury bills (see Appendix D).

4 Policy experiments

Five key policy experiments derived from the literature are discussed here and compared with

a Business-As-Usual (BAU) scenario calibrated using parameters broadly estimated for the

EU from publicly available databases or literature (Appendix C). Household parameters in

the EU are derived from two micro-datasets, the EU-SILC and the HFCS, that provide detailed

information on classes and wealth levels (recent studies include Wol and Zacharias 2013; Carroll

et al. 2014). Banking and lending information is available at the European Central Bank's

Statistical Warehouse with detailed breakdown of tax and interest rates. Parameters dened in

equations using post-Keynesian assumptions have been derived from a long history of empirically

veried hypotheses that are neatly summarized in Godley and Lavoie (2007). The innovation

parameters (ξ) have been normalized and index to 1 to allow for comparisons to the BAU scenario

but can be extended to actual levels using the EU-KLEMS or WIOD datasets. Remaining

parameters are estimated from the Eurostat database.

The aim of these experiments is to track the impact of policies on total output, prices, level of

unemployment, capitalist and worker incomes, energy demand and emission levels.

• Reduction in consumption expenditure (LowCon): The literature on low or no-growth

(Jackson 2009; Victor 2012; Victor and Jackson 2013) claims that reducing demand will

result in a reduction of output and income levels and emissions. In this experiment gov-

ernment and household consumption is reduced by 10%.

• Damage function (DmgFunc): Following the literature on damage function (Nordhaus

1992; Tol 2002; Wahba and Hope 2006; Stern 2007; Hope 2011; Rezai et al. 2012; Pindyck

2013; Taylor and Foley 2014), emissions levels beyond a certain threshold ϕ are assumed to

result in a higher depreciation rate of capital stock. For this experiment, the depreciation

13

rate of δ is endogenized as follows:

δt = δ

(1 +Max

[GHGt − ϕ

ϕ, 0

])where ϕ is the emissions threshold given in parts per million by volume (ppmv) beyond

which emissions are assumed to damage capital stock.

• High share of renewable energy (HiRenew): The innovation literature suggests a shift

towards renewable energies (Trainer 1995; Dincer 2000; Tahvonen and Salo 2001; Varun

et al. 2009) for environmentally sustainable growth. This experiment increases the share

of renewable energy by 10% in total energy consumption. The aim of this experiment is

to test the output and distributional impacts of switching to a cleaner but more expensive

technology.

• Environmental tax on rms and households (TaxF and TaxH): The endogenous environ-

mental tax follows a similar logic as the damage function (Herber and Raga 1995; Marron

and Toder 2014). The government increases the tax relative to the level of targeted emis-

sions ϕ.

τt = τ

(1 +Max

[GHGt − ϕ

ϕ, 0

])(4.1)

As emissions increase beyond this threshold, taxes rise at an exponential rate feeding

back across the system through a reduction in demand. Two policy experiments that

are conducted are an endogenous prot tax on rms and an endogenous income tax on

households.

• Capital and Energy eciency (InnoK and InnoE): Capital and energy eciency increases

output without increasing direct input costs (Binswanger 2001; Yang and Nordhaus 2006;

Herring and Roy 2007). In the BAU scenario, the capital-to-output ratio ξY K and the

energy-to-output ratio ξKE are normalized and indexed to 1. In this experiment, both

the parameters are shocked exogenously resulting in an increase in eciency by 10% re-

spectively. A value of ξY K = 1.1 implies that lower capital is required to produce the

same level of output while a value of ξKE = 1.1 implies less energy is required per unit of

output.

14

Figure 4.1: Policy Experiments

(a) Real output (b) Unemployment rate

(c) Price of E (d) Price of Y

(e) Real disposable income (f) Capitalist-Worker functional income distribution

(g) Energy demand (h) GHG emissions

15

Table 4.1: Summary of policy experiments

Growth Distributions EnvironmentOutput Unemp. Real Income Func. Income Dist. Energy Emissions

LowCon ↓ ↑ ↓ ↓ ↓ ↓DmgFunc ↑ ↓ ↓ ↑ ↑ ↑HiRenew ∼ ∼ ∼ ∼ ∼ ↓TaxF ∼ ∼ ↓ ↑ ∼ ∼TaxH ∼ ∼ ↓ ∼ ∼ ∼InnoK ∼ ∼ ↑ ↓ ↓ ↓InnoE ∼ ∼ ↑ ↓ ↓ ↓

Note:∼within 2% of BAU, ↑more than 2% increase, ↓more than 2% decrease. Functional income distributioncalculated as capitalist/worker income.

The experiments are described in Figure 4.1. Figures 4.1a and 4.1b show that almost all sim-

ulations roughly stabilize to the pre-shock BAU level of output and unemployment, with the

exception of the LowCons and the DmgFunc experiments. Whereas the lower output in the

LowCons case is due to the postulated reduction in consumption expenditure and thus demand,

the DmgFunc experiment results counter-intuitively in higher output. This is due to the fact

that increasing the depreciation of capital raises the investment requirement for rms. Since

investment is part of nal demand and credit nancing is available due to endogenous money,

output rises and unemployment decreases.

Table 4.1 summarizes the results for all the experiments. It shows that neither the link between

output and distribution, nor the one with the environment is predetermined. In particular,

while the connection between output and unemployment conforms to the standard formulation

of Okun's law, the income level and the functional income distribution are not as clear-cut.

Regarding environmental aspects, the absolute decoupling of energy use and emissions from

output can be observed in this model in some cases.

The lower output in the low consumption scenario (LowCons) case coincides with higher un-

employment and lower incomes, but also lower energy consumption and reduced emission, as

expected. It also leads to a lower inequality between capital and labor income as a result of

lower prot margins for capitalists that decline more than the wages.

The higher output resulting from higher investment in the endogenous damage function (Dmg-

Func) experiment is accompanied by lower unemployment and higher energy use and more

greenhouse gas emissions. It also goes along with lower real disposable income and lower worker

income relative to capitalist income, which are a result of the price dynamics shown in Figures

4.1d and 4.1c. The higher level of loans increases prices as rms push the cost of loan repayment

on to the consumers for both energy (through demand) and for nal goods (higher nancing

costs), which leads to the lower real disposable income of households and redistributes away

from workers.

In the higher renewables share (HiRenew) case, which assumes a switch to renewable energy,

leaves output, all three aspects of distribution and energy use are unchanged. Emissions, how-

16

ever, decline, because of the less polluting energy production. A number of minor adaptations

accompany the restructuring of the capital stock away from non-renewable energy producers

and towards renewable energy production, such as a slight increase in the price of energy and

thus of nal goods and some redistribution towards capitalists. However, these eects are small,

so that the decline in emissions takes place virtually ceteris paribus with regard to the variables

investigated here.

An environmental taxing on households (TaxH ) and rms (TaxF ) increases with higher GHGs.

As a result real disposable incomes declines reducing output. Unemployment rises while energy

use and emissions fall slightly below BAU level. The dierence between the two experiments

lies in the eect on real incomes, which fall more when households are directly taxed as opposed

to rms. On the other hand the functional income distribution worsens in the rm tax scenario

while improving slightly in the household tax. The underlying causal mechanism can be inferred

from the price changes in Figures 4.1d and 4.1c. When rms are taxed (TaxF ), prices for both

energy and nal goods rise as the tax burden is passed on to consumers. As a consequence,

real incomes fall in the TaxF experiment but less than in the TaxH experiment. Thus capital-

ists partially increase the demand for goods through higher prots subsequently worsening the

functional income distribution while keeping the output demand relatively close to BAU level.

The nal two experiments, innovation in capital (InnoK ) and energy eciency (InnoE ), reduce

both energy demand and emissions while maintaining a stable output and stable unemployment.

At the same time, real incomes rise and the ratio of capitalist to worker disposable income falls.

These experiments thus come closest to the hat trick of scoring on all three fronts: output,

distribution and environment. The dynamics behind this result are the following: The InnoK

simulation lowers the capital required for goods production, and thus indirectly the energy

demand. The InnoE scenario shows similar outcomes although the transmission mechanism is

a simple price adjustment process resulting from a decline in energy costs.

5 Conclusions

This paper is motivated by the trilemma of growth, distribution and the environment currently

facing European economic policy. It develops a stock-ow consistent macro model of a closed

economy, which incorporates supply-side eects into a demand-driven model. The model en-

compasses all sectors of the economy. Two innovations are introduced: rst, energy production

is formulated in more detail compared to previous studies and second, the environment is ex-

plicitly introduced into the model. The stock-ow consistent framework ensures that accounting

principles are maintained and feedback eects across sectors are accounted for.

The model is calibrated to the European economy, and applied to ve environmental economic

policies typically discussed in the literature. The aim is to assess their eect on the three

aspects of output growth, distribution (comprising unemployment and the functional income

distribution), and environmental sustainability.

17

The results show that neither the link between output and distribution, nor the one with the

environment is predetermined. In particular, while the connection between output and un-

employment conforms to the standard formulation of Okun's law, the income level and the

functional income distribution are not as clear-cut. Similar macro level outcomes can be the re-

sult of very dierent underlying structural and distributional changes. Regarding environmental

aspects, the absolute decoupling of energy use and emissions from output can be observed in

this model in some cases.

In particular, four policies show dierent trade-os within the trilemma. The de-growth simula-

tion shows that the lower output leads to higher unemployment while at the same time reducing

inequality in the functional income distribution. If emissions feed back into the depreciation of

the capital stock as in the damage function experiment, this has the opposite eect: unemploy-

ment falls but the functional income distribution worsens for workers. At the same time, this is

the only policy which leads to higher emissions due to increased investment requirements. En-

vironmental taxes on households or rms have mainly distributive eects while leaving output

and emissions largely unchanged.

Three policies, however, are triple-win situations. Increasing the share of renewable energy

reduces emissions while leaving all other outcome variables virtually unchanged. Finally, inno-

vations in capital or in energy productivity reduce both energy use and emissions, while at the

same time raising real incomes and redistributing towards workers.

These ndings are, of course, to be interpreted with caution as they are derived from a stylized

model. However, they may give rst pointers in the complex, multi-dimensional policy space in

which environmental economic policy is located.

The model presented here can be extended to test for additional climate-related policies while

keeping track of the feedback eects. These for example can include endogenous growth, in-

novation and technical change, and endogenous counter-cyclical government spending. A key

area for advancement of this model is the inclusion of aspects of nancialization that indirectly

feedback into the real economy and subsequently the environment.

18

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22

A Macro accounts

Table A.1: Balance Sheet

Households Production FinancialGovt.

∑Unemp. Workers Capitalists Firms Energy Banks Central Bank

Capital stock +K +KX +KR +K

Inventories +IN +INX +INV

Bank Deposits +Dh +Dk −Db 0

Advances −Ab −A 0

Bills +BCB −B 0

Loans −Lf −LX − LR +L 0∑0 +V h +V k +V f +V X + V R 0 0 −V G +NV

23

TableA.2:TransitionFlowMatrix

Unemp.

Workers

Capitalists

Firms

Energy

CommercialBanks

CentralBank

Govt.

∑Current

Capital

Current

Capital

Current

Capital

Current

Capital

Consumption

−C

u−C

h−C

k+S

−G

0

Energy

−EB

+E

X+

ER

0

Wages

+W

B−W

B0

Investment

+I

+IX

+IR

−I

−IX

−IR

0

∆Inventories

+∆IN

−∆IN

+∆IN

X−

∆IN

X0

Unemp.Benets

+UB

−UB

0

Bankprots

+Π

b−

Πb

−Π

CB

+Π

CB

0

Firm

prots

+Π

f−

Πf

0

Energyprots

+Π

E−

ΠX

−Π

R0

Taxes

−T

h−T

k−T

f−T

X−

TR

+T

0

iAdvances

−raA

t−

1+raA

t−

10

iDeposits

+rdD

h t−

1+rdD

k t−

1−rdD

t−

10

iBills

+rbB

CB

t−

1−rbB

t−

10

iLoans

−rlL

f t−

1−rlL

X t−

1−

rlL

R t−

1+rlL

t−

10

∆Advances

+∆A

−∆A

0

∆Deposits

−∆D

h−

∆D

k+

∆D

0

∆Bills

+∆B

CB

−∆B

0

∆Loans

+∆L

f+

∆L

X+

∆L

R−

∆L

0∑

00

00

00

00

00

00

0

24

B Stocks and ows of the EU household sector

Table B.1: Household Balance Sheet (EUR Billions)

Category 2012-Q4 2013-Q4 ∆

Non nancial assetsNon-nancial assets 29,625 29,041 -584

(Housing wealth) 28,055 27,435 -620

Financial assets

Currency and deposits 7,046 7,225 179

Securities and derivatives 1,537 1,365 -172

Loans -6,196 -6,152 44

Shares and equities 4,310 4,858 543

Insurance and pension 5,939 6,184 -245

Other 195 169 -26

Net worth 42,456 42,685 229Source: ECB Monthly Bulletin May 2014

Table B.2: Household Flow of funds (EUR Billions)

Flows 2013-Q4

Total income (all sources) 7,059

Net social contributions receivable 182

Tax -962

Gross disposable income 6,279

Consumption -5,507

Gross savings 829

Consumption of xed capital -407

Net capital transfers -4

Change in worth of stocks -189

Net savings (∆ net worth) 229Source: ECB Monthly Bulletin May 2014

25

C BAU Parameters and Variables

Parameter Value Description SourceNk 5% Capitalists as a % of total population Wol and Zacharias 2013Ω 50% Baseline government expenditure as

percentage of outputEurostat 2015 Table gov_a_exp

ω 1 Unit labor cost Eurostat 2015 Tablenama_aux_ulc

α1 0.8 MPC out of income Eurostat 2015 Table nasa_kiα2 0.1 MPC out of wealth Carroll et al. 2014β 0.25 Rate of investment in capital stock Godley and Lavoie 2007δ 0.05 Rate of depreciation Godley and Lavoie 2007ν 0.8 Target capacity utilization ratio Godley and Lavoie 2007η 0.05 Own consumption of energy Eurostat 2015 Table nrg_100aτ 0.2 Tax rate Eurostat 2014σ 0.25 Target inventories to sales ratio Godley and Lavoie 2007,γ 0.2 Rate of investment in inventories Godley and Lavoie 2007,Eurostat

2015 Table nama_10_gdpθ 0.1 Markup on costs Gullstrand et al. 2011ε 0.6 Poverty line relative to median income European Union denition of

poverty lineφ 0.05 GHG absorption rate IPCC 2007, 2012rl 0.04 Interest on loans European Central Bank 2015

Monetary and nancial statisticsrd 0.02 Interest on deposits European Central Bank 2015

Monetary and nancial statisticsrb 0.02 Interest on treasury bills European Central Bank 2015

Monetary and nancial statisticsra 0.02 Interest on advances European Central Bank 2015

Monetary and nancial statisticsξY K 1 Output to capital stock ratio

Baseline ratios normalized to 1ξKE 1 Capital stock to energy ratioξY N 1 Output to labor ratioξY G 1 Output to GHG ratio

Note: Parameters reect rounded averages of the last 5 years from specied data sources.

26

Variable Description

B Treasury bills

LR,LRN Liquidity Ratio (realized, notional)

c, C Consumption (real, nominal)

D Deposits

DR Debt requirement

ED,EB Energy demand, energy bill

g Nominal government expenditure

GHG Greenhouse Gasses

i, I Capital investment (real, nominal)

in, IN Inventories (real, nominal)

Inc Income

k,K Capital stock (real, nominal)

L Loans

M Money stock

p, pE Price, price of energy

Π Prots

s, S Sales (real, nominal)

u Capacity utilization rate

ub, UB Unemployment benets (real, nominal)

UC Unit cost

v, V Wealth (real, nominal)

WB Wage bill

X Non renewable input

y, Y Total rm output (real, nominal)

yd, Y D Disposable income (real, nominal)

27

D Financial sector

D.1 Commercial Banks

Commercial banks in the model are kept relatively simple. Holding deposits for households

against which loans are given out to the production sector.

Lbt = Lf

t + LXt + LR

t (D.1)

Dbt = Dk

t +Dht (D.2)

All loans as assumed to be provided on demand such that the total loans supplied equals Lbt

(D.1) against total household deposits Dbt (D.2). If the demand for loans exceeds the deposits

comercial banks hold, the remaining balance is borrowed from the central bank as advances at

an interest rate of ra. The value of advances equals:

Abt = Max[Lb

t −Dbt , 0] (D.3)

The Max condition implies that commercial banks only borrow if liabilities exceed deposits.

Bank prots are derived as

Πbt = rlL

bt−1 − rdDb

t−1 − raAbt−1 (D.4)

which equal interest received on loans less interest paid on deposits and advances (D.4). As part

of the borrowing and lending interest rate norms, the interest rate on loans are kept higher than

the interest rate on deposits such that rl ≥ rd. Prots are distributed to capitalist households.

D.2 Central Bank

In the model, the central bank is assumed that acts as the nancial arm of the government rather

than an independent regulator authority. The central bank issues advances to commercial banks

on demand such that

ACBt = Ab

t (D.5)

The central bank is also assumed to purchase any Treasury Bills issued by the government:

TBCBt = TBt (D.6)

28

Prots earned by the central bank equal:

ΠCBt = rbTB

CBt−1 + raA

CBt−1 (D.7)

Which are fully redistributed to the government.

29

INSTITUTE FORECOLOGICALECONOMICSVienna University ofEconomics and Business

WU ViennaInstitute for Ecological Economics

Welthandelsplatz 1/D4A-1020 Vienna

+43 (0)1 313 36 4848ecolecon@wu.ac.at